Understand the market behind your shortlist.
Compare buying conditions, test your budget, and explore model predictions alongside their actual outcomes.
Market tools and forecast evaluations cover the eight research cities. Compare prices and historical changes across all 25 cities →
Choose your cities
Compare up to three of the eight research cities.
How competitive is the market?
Compare homes for sale and time to reach a contract. Look at the same season a year earlier to put today’s conditions in context.
Latest captured market, rent and mortgage update
Checking the source archive… The reviewed history below keeps its published dates.
Jun 2026–Aug 2026Three-month rolling window
Start with a city
Choose one to three cities above. You’ll see the same home type and observation window for each.
Use this when you review a listing
More available homes and longer marketing times can give you more options to investigate. Ask how the actual property compares with other listings in its price range. These city observations do not predict your offer’s outcome.
What the data and research support
Redfin’s sales and prices cover completed sales; contract time covers homes going under contract. Those populations differ. Inventory is the count at period end. Rolling windows overlap, so adding them would double-count activity. A changing median price can reflect the mix of homes sold.
Year-earlier differences are calculated from retained levels. The two-direction summary appears only when both periods have at least ten closed sales and the two required measures. It describes the observations, with no fitted score or forecast.
Listing behavior motivated this view. The Federal Reserve listing study and buyer-search study use richer inputs and different geographies. This view is not a replication of those forecasts.
Redfin definitionsResearch and data coverageDownload the evidence
Will homes take longer to reach a contract?
Apply four ways of thinking about the market. Compare what each predicts for the next quarter, then inspect its past misses.
One clear target: days from listing to contract
Longer contract times may give buyers more time to compare listings. This forecasts a city’s median for a calendar quarter, not a particular home’s selling time or price.
No added model earned selection. Same season remains the baseline. See the historical comparison below.
Oct–Dec 2026Frozen on 2026-09-16
Current blend: Same season 100%.
Apply models and adjust their weights
Weights express your scenario. They are normalized to 100%; they are not probabilities. Changing them recomputes the historical comparison too. This experiment is separate from the annual price-forecast weights.
Current pace
Contract time stays at the latest observed pace.
The most recent eligible three-month window.Same season
Next quarter resembles the same quarter last year.
The same calendar quarter one year earlier. The retained baseline.Contract-time trend
Recent changes in contract speed help explain what comes next.
Changes in contract days over three months and one year; fitted on other California cities.Supply & demand
Homes available and the flow of new listings and contracts add information.
Contract-time trends, inventory relative to sales, inventory and sales growth, and pending contracts relative to new listings.Choose cities above to apply the models
Start with places you are considering. Each forecast uses the same home type, quarter and weights.
How large were the misses?
The selection period chose the baseline. Later history checks that decision without changing it. Both are exploratory replays using today’s revised source history and an assumed one-month reporting allowance.
Choose cities and nonzero weights to inspect comparable errors. Missing or thin rows are excluded from all models equally.
Full study comparison and selection rule
| Model | Selection period | Later replay |
|---|---|---|
| Current pace | 7 days | 5.8 days |
| Same season | 9.8 days | 5.2 days |
| Contract-time trend | 7.6 days | 5.7 days |
| Supply & demand | 6.6 days | 5.3 days |
| Equal blend | 6.7 days | 4.7 days |
No candidate passed the prespecified sample, improvement and consistency gate. Retain same-season baseline. A candidate must improve average error at least 10% against both simple baselines, beat same season in at least 7 of 12 origins, and meet the minimum local sample. The sample gate passed.
The selection period has 96 comparable rows and 12 origins; later replay has 136 rows and 17 origins. There are no random city-row splits, and training targets end before each input cutoff. Other California cities can still share regional shocks.
Coefficient fitting uses 299 other California cities; our eight cities are evaluated separately. Neighboring markets are correlated, so city counts overstate independent evidence.
October–December 2026: keep the prediction, check the outcome
Thirteen city/home-type forecasts were frozen before October 1. Each week, the data worker captures source evidence. After December 31, it locks each first eligible outcome and reports errors. Thin or missing outcomes remain pending.
Checking the capture record…
Capture status and locked outcomesLatest captured observations and sources
Download the study and source referencesFrozen October–December predictionsWhat remains untested
Source: Redfin Data Center, retrieved 2026-09-16. Contract-time medians and closed-sales counts describe different transaction populations. The ten-sale quality rule is not a calibrated uncertainty claim. Public 2025 outcomes were already inspected; this is not an untouched historical test.
What could owning cost you?
Start with a home price and rent for a comparable home. See the monthly budget, equity built through repayments, and how your assumptions change the longer-term comparison.
What price fits your monthly limit and cash?
Uses the down payment, financing, taxes, upkeep, insurance, HOA and buying fees above. Enter cash set aside for the purchase after keeping your emergency reserves. This estimates a spending limit, not lender approval.
Enter both budgets and valid cost assumptions to calculate a price limit. Mortgage insurance must be specified when required above.
Explore mortgage rates and purchasing power over time
Freddie Mac PMMS, retrieved from FRED, Federal Reserve Bank of St. Louis. 2,894 weekly observations through 2026-09-10. This national conforming-loan benchmark is not a quote for a Bay Area jumbo borrower. The method changed on November 17, 2022.
6.76% on 2026-09-10, the last available observation in 2026. At that fixed rate a $100,000, 30-year loan has a $649 monthly principal-and-interest payment, before all other costs.
National 30-year mortgage rate history
Annual interest rate, percent. 1971-04 to 2026-09.
View exact values (666 periods)
| Month | Monthly average of observed weekly rates |
|---|---|
| 2026-09 | 6.73% |
| 2026-08 | 6.67% |
| 2026-07 | 6.54% |
| 2026-06 | 6.49% |
| 2026-05 | 6.44% |
| 2026-04 | 6.33% |
| 2026-03 | 6.18% |
| 2026-02 | 6.05% |
| 2026-01 | 6.10% |
| 2025-12 | 6.19% |
| 2025-11 | 6.24% |
| 2025-10 | 6.25% |
| 2025-09 | 6.35% |
| 2025-08 | 6.59% |
| 2025-07 | 6.72% |
| 2025-06 | 6.82% |
| 2025-05 | 6.82% |
| 2025-04 | 6.72% |
| 2025-03 | 6.65% |
| 2025-02 | 6.84% |
| 2025-01 | 6.96% |
| 2024-12 | 6.71% |
| 2024-11 | 6.80% |
| 2024-10 | 6.43% |
| 2024-09 | 6.18% |
| 2024-08 | 6.50% |
| 2024-07 | 6.85% |
| 2024-06 | 6.92% |
| 2024-05 | 7.06% |
| 2024-04 | 6.99% |
| 2024-03 | 6.82% |
| 2024-02 | 6.78% |
| 2024-01 | 6.64% |
| 2023-12 | 6.81% |
| 2023-11 | 7.44% |
| 2023-10 | 7.62% |
| 2023-09 | 7.20% |
| 2023-08 | 7.07% |
| 2023-07 | 6.84% |
| 2023-06 | 6.71% |
| 2023-05 | 6.42% |
| 2023-04 | 6.34% |
| 2023-03 | 6.54% |
| 2023-02 | 6.26% |
| 2023-01 | 6.27% |
| 2022-12 | 6.36% |
| 2022-11 | 6.80% |
| 2022-10 | 6.90% |
| 2022-09 | 6.11% |
| 2022-08 | 5.22% |
| 2022-07 | 5.41% |
| 2022-06 | 5.52% |
| 2022-05 | 5.23% |
| 2022-04 | 4.98% |
| 2022-03 | 4.17% |
| 2022-02 | 3.76% |
| 2022-01 | 3.45% |
| 2021-12 | 3.10% |
| 2021-11 | 3.07% |
| 2021-10 | 3.07% |
| 2021-09 | 2.90% |
| 2021-08 | 2.84% |
| 2021-07 | 2.87% |
| 2021-06 | 2.98% |
| 2021-05 | 2.96% |
| 2021-04 | 3.06% |
| 2021-03 | 3.08% |
| 2021-02 | 2.81% |
| 2021-01 | 2.73% |
| 2020-12 | 2.68% |
| 2020-11 | 2.77% |
| 2020-10 | 2.83% |
| 2020-09 | 2.89% |
| 2020-08 | 2.94% |
| 2020-07 | 3.02% |
| 2020-06 | 3.16% |
| 2020-05 | 3.23% |
| 2020-04 | 3.31% |
| 2020-03 | 3.45% |
| 2020-02 | 3.46% |
| 2020-01 | 3.62% |
| 2019-12 | 3.72% |
| 2019-11 | 3.69% |
| 2019-10 | 3.69% |
| 2019-09 | 3.61% |
| 2019-08 | 3.62% |
| 2019-07 | 3.77% |
| 2019-06 | 3.80% |
| 2019-05 | 4.07% |
| 2019-04 | 4.14% |
| 2019-03 | 4.26% |
| 2019-02 | 4.37% |
| 2019-01 | 4.46% |
| 2018-12 | 4.64% |
| 2018-11 | 4.87% |
| 2018-10 | 4.83% |
| 2018-09 | 4.63% |
| 2018-08 | 4.55% |
| 2018-07 | 4.53% |
| 2018-06 | 4.57% |
| 2018-05 | 4.59% |
| 2018-04 | 4.47% |
| 2018-03 | 4.44% |
| 2018-02 | 4.33% |
| 2018-01 | 4.03% |
| 2017-12 | 3.95% |
| 2017-11 | 3.92% |
| 2017-10 | 3.90% |
| 2017-09 | 3.81% |
| 2017-08 | 3.88% |
| 2017-07 | 3.97% |
| 2017-06 | 3.90% |
| 2017-05 | 4.01% |
| 2017-04 | 4.04% |
| 2017-03 | 4.20% |
| 2017-02 | 4.17% |
| 2017-01 | 4.15% |
| 2016-12 | 4.20% |
| 2016-11 | 3.77% |
| 2016-10 | 3.47% |
| 2016-09 | 3.46% |
| 2016-08 | 3.44% |
| 2016-07 | 3.44% |
| 2016-06 | 3.57% |
| 2016-05 | 3.60% |
| 2016-04 | 3.60% |
| 2016-03 | 3.69% |
| 2016-02 | 3.66% |
| 2016-01 | 3.87% |
| 2015-12 | 3.96% |
| 2015-11 | 3.94% |
| 2015-10 | 3.80% |
| 2015-09 | 3.89% |
| 2015-08 | 3.90% |
| 2015-07 | 4.05% |
| 2015-06 | 3.98% |
| 2015-05 | 3.84% |
| 2015-04 | 3.67% |
| 2015-03 | 3.77% |
| 2015-02 | 3.71% |
| 2015-01 | 3.67% |
| 2014-12 | 3.86% |
| 2014-11 | 4.00% |
| 2014-10 | 4.04% |
| 2014-09 | 4.16% |
| 2014-08 | 4.12% |
| 2014-07 | 4.13% |
| 2014-06 | 4.16% |
| 2014-05 | 4.19% |
| 2014-04 | 4.34% |
| 2014-03 | 4.34% |
| 2014-02 | 4.30% |
| 2014-01 | 4.43% |
| 2013-12 | 4.46% |
| 2013-11 | 4.25% |
| 2013-10 | 4.19% |
| 2013-09 | 4.49% |
| 2013-08 | 4.46% |
| 2013-07 | 4.37% |
| 2013-06 | 4.07% |
| 2013-05 | 3.54% |
| 2013-04 | 3.45% |
| 2013-03 | 3.57% |
| 2013-02 | 3.53% |
| 2013-01 | 3.41% |
| 2012-12 | 3.35% |
| 2012-11 | 3.35% |
| 2012-10 | 3.38% |
| 2012-09 | 3.50% |
| 2012-08 | 3.60% |
| 2012-07 | 3.55% |
| 2012-06 | 3.67% |
| 2012-05 | 3.80% |
| 2012-04 | 3.91% |
| 2012-03 | 3.95% |
| 2012-02 | 3.89% |
| 2012-01 | 3.92% |
| 2011-12 | 3.96% |
| 2011-11 | 3.99% |
| 2011-10 | 4.07% |
| 2011-09 | 4.11% |
| 2011-08 | 4.27% |
| 2011-07 | 4.54% |
| 2011-06 | 4.51% |
| 2011-05 | 4.64% |
| 2011-04 | 4.84% |
| 2011-03 | 4.84% |
| 2011-02 | 4.95% |
| 2011-01 | 4.75% |
| 2010-12 | 4.71% |
| 2010-11 | 4.30% |
| 2010-10 | 4.23% |
| 2010-09 | 4.35% |
| 2010-08 | 4.43% |
| 2010-07 | 4.56% |
| 2010-06 | 4.74% |
| 2010-05 | 4.89% |
| 2010-04 | 5.10% |
| 2010-03 | 4.97% |
| 2010-02 | 4.99% |
| 2010-01 | 5.03% |
| 2009-12 | 4.93% |
| 2009-11 | 4.88% |
| 2009-10 | 4.95% |
| 2009-09 | 5.06% |
| 2009-08 | 5.19% |
| 2009-07 | 5.22% |
| 2009-06 | 5.42% |
| 2009-05 | 4.86% |
| 2009-04 | 4.81% |
| 2009-03 | 5.00% |
| 2009-02 | 5.13% |
| 2009-01 | 5.05% |
| 2008-12 | 5.29% |
| 2008-11 | 6.09% |
| 2008-10 | 6.20% |
| 2008-09 | 6.04% |
| 2008-08 | 6.48% |
| 2008-07 | 6.43% |
| 2008-06 | 6.32% |
| 2008-05 | 6.04% |
| 2008-04 | 5.92% |
| 2008-03 | 5.97% |
| 2008-02 | 5.92% |
| 2008-01 | 5.76% |
| 2007-12 | 6.10% |
| 2007-11 | 6.21% |
| 2007-10 | 6.38% |
| 2007-09 | 6.38% |
| 2007-08 | 6.57% |
| 2007-07 | 6.70% |
| 2007-06 | 6.66% |
| 2007-05 | 6.26% |
| 2007-04 | 6.18% |
| 2007-03 | 6.16% |
| 2007-02 | 6.29% |
| 2007-01 | 6.22% |
| 2006-12 | 6.13% |
| 2006-11 | 6.24% |
| 2006-10 | 6.36% |
| 2006-09 | 6.40% |
| 2006-08 | 6.52% |
| 2006-07 | 6.76% |
| 2006-06 | 6.68% |
| 2006-05 | 6.60% |
| 2006-04 | 6.51% |
| 2006-03 | 6.32% |
| 2006-02 | 6.25% |
| 2006-01 | 6.15% |
| 2005-12 | 6.27% |
| 2005-11 | 6.33% |
| 2005-10 | 6.06% |
| 2005-09 | 5.77% |
| 2005-08 | 5.82% |
| 2005-07 | 5.70% |
| 2005-06 | 5.58% |
| 2005-05 | 5.72% |
| 2005-04 | 5.86% |
| 2005-03 | 5.93% |
| 2005-02 | 5.63% |
| 2005-01 | 5.71% |
| 2004-12 | 5.75% |
| 2004-11 | 5.73% |
| 2004-10 | 5.72% |
| 2004-09 | 5.75% |
| 2004-08 | 5.87% |
| 2004-07 | 6.06% |
| 2004-06 | 6.29% |
| 2004-05 | 6.27% |
| 2004-04 | 5.83% |
| 2004-03 | 5.45% |
| 2004-02 | 5.63% |
| 2004-01 | 5.71% |
| 2003-12 | 5.88% |
| 2003-11 | 5.93% |
| 2003-10 | 5.95% |
| 2003-09 | 6.15% |
| 2003-08 | 6.26% |
| 2003-07 | 5.63% |
| 2003-06 | 5.23% |
| 2003-05 | 5.48% |
| 2003-04 | 5.81% |
| 2003-03 | 5.75% |
| 2003-02 | 5.84% |
| 2003-01 | 5.92% |
| 2002-12 | 6.05% |
| 2002-11 | 6.07% |
| 2002-10 | 6.11% |
| 2002-09 | 6.09% |
| 2002-08 | 6.29% |
| 2002-07 | 6.49% |
| 2002-06 | 6.65% |
| 2002-05 | 6.81% |
| 2002-04 | 6.99% |
| 2002-03 | 7.01% |
| 2002-02 | 6.89% |
| 2002-01 | 7.00% |
| 2001-12 | 7.07% |
| 2001-11 | 6.66% |
| 2001-10 | 6.62% |
| 2001-09 | 6.82% |
| 2001-08 | 6.95% |
| 2001-07 | 7.13% |
| 2001-06 | 7.16% |
| 2001-05 | 7.14% |
| 2001-04 | 7.08% |
| 2001-03 | 6.95% |
| 2001-02 | 7.05% |
| 2001-01 | 7.03% |
| 2000-12 | 7.38% |
| 2000-11 | 7.75% |
| 2000-10 | 7.79% |
| 2000-09 | 7.91% |
| 2000-08 | 8.03% |
| 2000-07 | 8.15% |
| 2000-06 | 8.29% |
| 2000-05 | 8.51% |
| 2000-04 | 8.15% |
| 2000-03 | 8.24% |
| 2000-02 | 8.33% |
| 2000-01 | 8.21% |
| 1999-12 | 7.91% |
| 1999-11 | 7.74% |
| 1999-10 | 7.85% |
| 1999-09 | 7.82% |
| 1999-08 | 7.94% |
| 1999-07 | 7.63% |
| 1999-06 | 7.55% |
| 1999-05 | 7.15% |
| 1999-04 | 6.92% |
| 1999-03 | 7.04% |
| 1999-02 | 6.81% |
| 1999-01 | 6.79% |
| 1998-12 | 6.74% |
| 1998-11 | 6.87% |
| 1998-10 | 6.71% |
| 1998-09 | 6.72% |
| 1998-08 | 6.92% |
| 1998-07 | 6.95% |
| 1998-06 | 7.00% |
| 1998-05 | 7.14% |
| 1998-04 | 7.14% |
| 1998-03 | 7.13% |
| 1998-02 | 7.04% |
| 1998-01 | 6.99% |
| 1997-12 | 7.10% |
| 1997-11 | 7.21% |
| 1997-10 | 7.29% |
| 1997-09 | 7.43% |
| 1997-08 | 7.48% |
| 1997-07 | 7.50% |
| 1997-06 | 7.69% |
| 1997-05 | 7.94% |
| 1997-04 | 8.14% |
| 1997-03 | 7.90% |
| 1997-02 | 7.65% |
| 1997-01 | 7.82% |
| 1996-12 | 7.60% |
| 1996-11 | 7.62% |
| 1996-10 | 7.92% |
| 1996-09 | 8.23% |
| 1996-08 | 8.00% |
| 1996-07 | 8.25% |
| 1996-06 | 8.32% |
| 1996-05 | 8.07% |
| 1996-04 | 7.93% |
| 1996-03 | 7.62% |
| 1996-02 | 7.08% |
| 1996-01 | 7.03% |
| 1995-12 | 7.20% |
| 1995-11 | 7.38% |
| 1995-10 | 7.47% |
| 1995-09 | 7.64% |
| 1995-08 | 7.86% |
| 1995-07 | 7.61% |
| 1995-06 | 7.57% |
| 1995-05 | 7.96% |
| 1995-04 | 8.32% |
| 1995-03 | 8.46% |
| 1995-02 | 8.83% |
| 1995-01 | 9.15% |
| 1994-12 | 9.20% |
| 1994-11 | 9.17% |
| 1994-10 | 8.93% |
| 1994-09 | 8.64% |
| 1994-08 | 8.51% |
| 1994-07 | 8.61% |
| 1994-06 | 8.40% |
| 1994-05 | 8.60% |
| 1994-04 | 8.32% |
| 1994-03 | 7.67% |
| 1994-02 | 7.15% |
| 1994-01 | 7.06% |
| 1993-12 | 7.17% |
| 1993-11 | 7.16% |
| 1993-10 | 6.83% |
| 1993-09 | 6.92% |
| 1993-08 | 7.11% |
| 1993-07 | 7.21% |
| 1993-06 | 7.42% |
| 1993-05 | 7.46% |
| 1993-04 | 7.47% |
| 1993-03 | 7.50% |
| 1993-02 | 7.68% |
| 1993-01 | 7.99% |
| 1992-12 | 8.21% |
| 1992-11 | 8.30% |
| 1992-10 | 8.09% |
| 1992-09 | 7.92% |
| 1992-08 | 7.97% |
| 1992-07 | 8.13% |
| 1992-06 | 8.51% |
| 1992-05 | 8.67% |
| 1992-04 | 8.85% |
| 1992-03 | 8.93% |
| 1992-02 | 8.76% |
| 1992-01 | 8.43% |
| 1991-12 | 8.50% |
| 1991-11 | 8.71% |
| 1991-10 | 8.86% |
| 1991-09 | 9.01% |
| 1991-08 | 9.24% |
| 1991-07 | 9.57% |
| 1991-06 | 9.62% |
| 1991-05 | 9.47% |
| 1991-04 | 9.49% |
| 1991-03 | 9.50% |
| 1991-02 | 9.37% |
| 1991-01 | 9.64% |
| 1990-12 | 9.67% |
| 1990-11 | 10.01% |
| 1990-10 | 10.18% |
| 1990-09 | 10.18% |
| 1990-08 | 10.10% |
| 1990-07 | 10.04% |
| 1990-06 | 10.16% |
| 1990-05 | 10.48% |
| 1990-04 | 10.37% |
| 1990-03 | 10.27% |
| 1990-02 | 10.20% |
| 1990-01 | 9.89% |
| 1989-12 | 9.74% |
| 1989-11 | 9.77% |
| 1989-10 | 9.95% |
| 1989-09 | 10.13% |
| 1989-08 | 9.98% |
| 1989-07 | 9.88% |
| 1989-06 | 10.20% |
| 1989-05 | 10.77% |
| 1989-04 | 11.05% |
| 1989-03 | 11.03% |
| 1989-02 | 10.64% |
| 1989-01 | 10.73% |
| 1988-12 | 10.61% |
| 1988-11 | 10.27% |
| 1988-10 | 10.30% |
| 1988-09 | 10.48% |
| 1988-08 | 10.60% |
| 1988-07 | 10.43% |
| 1988-06 | 10.46% |
| 1988-05 | 10.46% |
| 1988-04 | 10.20% |
| 1988-03 | 9.93% |
| 1988-02 | 9.89% |
| 1988-01 | 10.38% |
| 1987-12 | 10.64% |
| 1987-11 | 10.65% |
| 1987-10 | 11.26% |
| 1987-09 | 10.89% |
| 1987-08 | 10.33% |
| 1987-07 | 10.28% |
| 1987-06 | 10.54% |
| 1987-05 | 10.60% |
| 1987-04 | 9.83% |
| 1987-03 | 9.04% |
| 1987-02 | 9.08% |
| 1987-01 | 9.20% |
| 1986-12 | 9.31% |
| 1986-11 | 9.70% |
| 1986-10 | 9.97% |
| 1986-09 | 10.01% |
| 1986-08 | 10.20% |
| 1986-07 | 10.51% |
| 1986-06 | 10.68% |
| 1986-05 | 10.14% |
| 1986-04 | 9.94% |
| 1986-03 | 10.08% |
| 1986-02 | 10.71% |
| 1986-01 | 10.89% |
| 1985-12 | 11.26% |
| 1985-11 | 11.78% |
| 1985-10 | 12.13% |
| 1985-09 | 12.19% |
| 1985-08 | 12.19% |
| 1985-07 | 12.03% |
| 1985-06 | 12.21% |
| 1985-05 | 12.91% |
| 1985-04 | 13.19% |
| 1985-03 | 13.17% |
| 1985-02 | 12.92% |
| 1985-01 | 13.07% |
| 1984-12 | 13.18% |
| 1984-11 | 13.64% |
| 1984-10 | 14.13% |
| 1984-09 | 14.35% |
| 1984-08 | 14.47% |
| 1984-07 | 14.67% |
| 1984-06 | 14.42% |
| 1984-05 | 13.94% |
| 1984-04 | 13.65% |
| 1984-03 | 13.39% |
| 1984-02 | 13.23% |
| 1984-01 | 13.37% |
| 1983-12 | 13.42% |
| 1983-11 | 13.44% |
| 1983-10 | 13.53% |
| 1983-09 | 13.73% |
| 1983-08 | 13.81% |
| 1983-07 | 13.42% |
| 1983-06 | 12.87% |
| 1983-05 | 12.63% |
| 1983-04 | 12.78% |
| 1983-03 | 12.80% |
| 1983-02 | 13.04% |
| 1983-01 | 13.25% |
| 1982-12 | 13.62% |
| 1982-11 | 13.82% |
| 1982-10 | 14.61% |
| 1982-09 | 15.43% |
| 1982-08 | 16.27% |
| 1982-07 | 16.82% |
| 1982-06 | 16.70% |
| 1982-05 | 16.68% |
| 1982-04 | 16.89% |
| 1982-03 | 17.16% |
| 1982-02 | 17.60% |
| 1982-01 | 17.48% |
| 1981-12 | 16.95% |
| 1981-11 | 17.83% |
| 1981-10 | 18.45% |
| 1981-09 | 18.16% |
| 1981-08 | 17.29% |
| 1981-07 | 16.83% |
| 1981-06 | 16.70% |
| 1981-05 | 16.40% |
| 1981-04 | 15.58% |
| 1981-03 | 15.40% |
| 1981-02 | 15.13% |
| 1981-01 | 14.90% |
| 1980-12 | 14.79% |
| 1980-11 | 14.21% |
| 1980-10 | 13.79% |
| 1980-09 | 13.20% |
| 1980-08 | 12.56% |
| 1980-07 | 12.19% |
| 1980-06 | 12.71% |
| 1980-05 | 14.26% |
| 1980-04 | 16.33% |
| 1980-03 | 15.28% |
| 1980-02 | 13.04% |
| 1980-01 | 12.88% |
| 1979-12 | 12.90% |
| 1979-11 | 12.83% |
| 1979-10 | 11.64% |
| 1979-09 | 11.30% |
| 1979-08 | 11.09% |
| 1979-07 | 11.09% |
| 1979-06 | 11.04% |
| 1979-05 | 10.69% |
| 1979-04 | 10.50% |
| 1979-03 | 10.43% |
| 1979-02 | 10.41% |
| 1979-01 | 10.39% |
| 1978-12 | 10.35% |
| 1978-11 | 10.11% |
| 1978-10 | 9.86% |
| 1978-09 | 9.76% |
| 1978-08 | 9.79% |
| 1978-07 | 9.74% |
| 1978-06 | 9.71% |
| 1978-05 | 9.57% |
| 1978-04 | 9.36% |
| 1978-03 | 9.20% |
| 1978-02 | 9.14% |
| 1978-01 | 9.02% |
| 1977-12 | 8.96% |
| 1977-11 | 8.92% |
| 1977-10 | 8.92% |
| 1977-09 | 8.90% |
| 1977-08 | 8.94% |
| 1977-07 | 8.94% |
| 1977-06 | 8.86% |
| 1977-05 | 8.83% |
| 1977-04 | 8.75% |
| 1977-03 | 8.69% |
| 1977-02 | 8.67% |
| 1977-01 | 8.72% |
| 1976-12 | 8.79% |
| 1976-11 | 8.81% |
| 1976-10 | 8.93% |
| 1976-09 | 8.98% |
| 1976-08 | 9.00% |
| 1976-07 | 8.93% |
| 1976-06 | 8.85% |
| 1976-05 | 8.77% |
| 1976-04 | 8.73% |
| 1976-03 | 8.75% |
| 1976-02 | 8.81% |
| 1976-01 | 9.02% |
| 1975-12 | 9.10% |
| 1975-11 | 9.14% |
| 1975-10 | 9.22% |
| 1975-09 | 9.13% |
| 1975-08 | 8.94% |
| 1975-07 | 8.89% |
| 1975-06 | 8.89% |
| 1975-05 | 8.91% |
| 1975-04 | 8.82% |
| 1975-03 | 8.90% |
| 1975-02 | 9.11% |
| 1975-01 | 9.43% |
| 1974-12 | 9.62% |
| 1974-11 | 9.79% |
| 1974-10 | 9.98% |
| 1974-09 | 9.96% |
| 1974-08 | 9.59% |
| 1974-07 | 9.28% |
| 1974-06 | 9.09% |
| 1974-05 | 8.97% |
| 1974-04 | 8.58% |
| 1974-03 | 8.41% |
| 1974-02 | 8.46% |
| 1974-01 | 8.54% |
| 1973-12 | 8.54% |
| 1973-11 | 8.58% |
| 1973-10 | 8.77% |
| 1973-09 | 8.81% |
| 1973-08 | 8.50% |
| 1973-07 | 8.05% |
| 1973-06 | 7.73% |
| 1973-05 | 7.65% |
| 1973-04 | 7.54% |
| 1973-03 | 7.46% |
| 1973-02 | 7.44% |
| 1973-01 | 7.44% |
| 1972-12 | 7.44% |
| 1972-11 | 7.43% |
| 1972-10 | 7.42% |
| 1972-09 | 7.42% |
| 1972-08 | 7.40% |
| 1972-07 | 7.39% |
| 1972-06 | 7.37% |
| 1972-05 | 7.37% |
| 1972-04 | 7.29% |
| 1972-03 | 7.30% |
| 1972-02 | 7.32% |
| 1972-01 | 7.44% |
| 1971-12 | 7.48% |
| 1971-11 | 7.55% |
| 1971-10 | 7.63% |
| 1971-09 | 7.69% |
| 1971-08 | 7.70% |
| 1971-07 | 7.60% |
| 1971-06 | 7.53% |
| 1971-05 | 7.43% |
| 1971-04 | 7.31% |
Monthly chart values average the observations dated in each month; the latest month can be partial. These are current-vintage data. A historical rate applied to today’s price is a scenario, not a reconstruction of historical affordability.
Why rents and ownership costs belong in the lab
They make the price of a home easier to interpret. They also give us a separate longer-term hypothesis to test. Your cost assumptions do not become an appreciation forecast or a weight in the forecast mixer.
Research on prices and rentsResearch on ownership costData coverage and limits
Is housing keeping up with local growth?
See how employment and the number of homes changed. Housing-stock totals let us compare construction across cities of different sizes.
Housing: January 1. Jobs: Q2 snapshot. Completions: full calendar year.All housing types. Job history currently ends in 2023.
Choose cities to compare their growth
We’ll align the selected year and show missing observations explicitly.
The idea we’re testing
Stronger demand may translate into higher prices when housing responds slowly. A useful test needs both sides of that relationship. Low construction on its own can also reflect weak demand.
Evidence, gaps and the next test
Federal Reserve research on jobs and construction constraints supports studying the interaction. It does not establish a forecast for these cities.
The new stock history closes a denominator gap. The proposed multi-year forecasting study still has too few mature observations under its source-lag assumptions. Two completion years remain withheld: San Bruno 2020 and South San Francisco 2024. We need documented historical availability and broader coverage before a new predictive test.
DOF estimates include vacant homes and revisions. We use January snapshots consistently and reconcile the overlapping April 2020 benchmarks. Geography definitions across DOF, Census and city completion reports also need care. All charts are reconstructed from the retained releases.
Housing-stock sourcesJobs and completion sourcesDownload the evidence
Explore a thesis, then check its record
The current annual forecasts use three price and tax-base signals. None earned selection over matching the county. The new Market outlook predicts contract time in days. It has its own weights and track record; cost scenarios and jobs/housing evidence also answer different questions.
See each family’s research and validation status →This scenario link is invalid or refers to an unsupported version. Choose cities and weights to start a new scenario.
Understand the models, then choose weights
These three models test price and tax-base signals. Each learns a relationship from earlier data, then estimates the city's next-year home-value growth relative to San Mateo County. An input is not itself a prediction.
None passed the original selection test. “Match the county” remains the selected baseline. The models share data and a study design; agreement is not independent confirmation.
Recent price performance
Does how a city performed recently help predict its next year?
- What it measures
- The city's home-value growth over the past 12 months, minus San Mateo County's growth over those same months.
- Made-up example · input only
- City values rise 12% and county values rise 8%. The input is +4 percentage points of recent outperformance.
- How to interpret it
- The fitted relationship can favor a reversal. This model does not simply predict that recent winners keep winning; “Repeat recent relative growth” is the separate rule that does that.
Exact input calculation and earlier test
City 12-month percentage change − county 12-month percentage change.
Average absolute prediction error in the earlier model-selection test: 1.601 percentage points. County baseline: 1.346. Lower is better; selection also required consistency across years.
Price gap versus history
Does a change in a city's usual price relationship to the county help predict its next year?
- What it measures
- Today's city-to-county home-value ratio, compared with its average over the preceding 60 months.
- Made-up example · input only
- The city's index is 80% of the county index today, versus an average of 88% previously. The model's gap input is +10%: 88 ÷ 80 − 1.
- How to interpret it
- This measures relative price level, not relative growth or affordability. A positive gap is not proof of a bargain and does not imply a 10% price rise.
Exact input calculation and earlier test
100 × (average of the preceding 60 monthly city/county ratios ÷ current ratio − 1). The current month is excluded from the average.
Average absolute prediction error in the earlier model-selection test: 1.398 percentage points. County baseline: 1.346. Lower is better; selection also required consistency across years.
Taxable property growth
Does growth in the taxable property base help predict home-value growth?
- What it measures
- Three-year growth in the city's net assessment roll, minus the county's growth. The roll is the taxable value of property, across property classes.
- Made-up example · input only
- The city's taxable property total grows 12% over three years and the county's grows 8%. The input is +4 percentage points.
- How to interpret it
- Tax rules and multiple property classes affect this total. It is not a home-price index, city revenue, or a direct measure of jobs or commercial growth.
Exact input calculation and earlier test
City three-year net assessment-roll percentage change − county change. Use January of the year before the July feature cutoff, with a three-year lookback. This assumed lag is not verified historical publication timing.
Average absolute prediction error in the earlier model-selection test: 1.392 percentage points. County baseline: 1.346. Lower is better; selection also required consistency across years.
A 50% weight means half of that model's prediction contributes to the mix. It does not mean a 50% chance the model is right. Zero removes a model; changing weights does not retrain it. The exact equal-weight average stays visible as a comparison.
Choose a city to inspect the models.
Methods, versions and source files
Component forecasts were issued 2026-09-15T02:02:10Z. model-lab-v1 uses the original housing-screen-v1 rules and data. Every model shares the same target, benchmark, home type, cutoff and horizon. A missing selected prediction withholds the blend; no weight is silently reassigned.
Earlier validation selected the county baseline. The original decision and paper record stay unchanged. Scores here are recomputed from blended predictions, not averaged component errors.
Download all component predictions, historical outcomes and source hashes · Read the original track record
Source manifest SHA-256: 46f922fcefd73314d74781232e4679632900b1fe429ec6af31c61ab00df388d7